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Composer streamlines clinical policy management with advanced features. Its Automated Decision Tree Creation uses AI to transform complex policies into actionable workflows, cutting drafting time by 75%. Seamless Policy Updates reduce update times by 70% through automatic ingestion of new policies and version tracking.

With Adaptive Learning, decision trees are customized based on user edits, improving accuracy and alignment with workflows. Comprehensive Audit Trails ensure transparency and compliance with detailed version histories. The platform’s Intuitive Interface includes a drag-and-drop editor and testing sandbox for accurate, confident deployment.

Composer uses Optical Character Recognition (OCR) and NLP to extract critical information from clinical policies. This data is mapped into structured decision trees, eliminating the need for manual input. By automating this process, Composer significantly reduces setup time, helping organizations draft decision trees 70% faster while ensuring every decision tree is accurate, comprehensive, and aligned with the latest standards.

Composer’s machine learning capabilities enhance efficiency and accuracy by learning from user edits to optimize decision tree creation, automatically adapting workflows to align with evolving payer policies and clinical data, and minimizing the risk of errors to ensure consistent decision-making. This adaptive approach empowers organizations to remain agile, maintain compliance, and prioritize patient care in a constantly changing regulatory landscape.

Composer ensures decision trees remain accurate and compliant by incorporating expiration dates that deactivate workflows when a policy is no longer active. When updated clinical policies are uploaded, Composer ingests the new information and generates a new version of the decision tree. This keeps workflows aligned with the latest payer requirements without causing disruptions. Decision trees can also be edited throughout the year to address evolving needs. Composer’s version tracking consolidates all changes in one place, simplifying the process of comparing updates, viewing differences, and maintaining a clear audit trail. By automating the update process, Composer reduces update times by 60%, eliminating manual revisions and enhancing compliance and operational efficiency.

Composer incorporates advanced machine learning to continuously improve decision tree accuracy and usability. By analyzing user edits and patterns in how decision trees are customized, Composer adapts to organizational workflows and preferences. Over time, this learning allows Composer to anticipate needs, automatically structuring decision trees that align with user-specific requirements while maintaining compliance with payer and regulatory guidelines.

Composer maintains a transparent version history and audit trail for all decision tree updates, ensuring workflows align with payer-specific standards. Its robust version tracking provides a detailed record of changes, enabling organizations to quickly respond to audits or compliance reviews. Composer also offers real-time updates and a testing sandbox, allowing users to validate changes before deployment. This ensures accuracy and confidence in decision-making while meeting the evolving requirements of payer policies.